Load Frequency Control & Automatic Voltage Regulation for a Single Area Power System

Since a Superconducting Magnetic Energy Storage (SMES) unit with a self–commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper presents a novel control method of SMES with a self-tuned Fuzzy Proportional Integral (FPI) controller associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self–tuning configuration of FPI controller in AGC on SMES control is compared with that of fixed gain PI controlled AGC. It is seen that with addition of FPI controller, SMES can perform a more effective primary frequency control for single area power system. Key words: Load frequency control; single area power system; automatic generation control; superconducting magnetic energy storage unit; fuzzy proportional integral controller

In this paper, combination of Generalized Fuzzy Model (GFM) and Gaussian Mixture Model (GMM) based controller is used to determine the optimal parameters of Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) system of single area power system. GFM combines the advantages of Takagi and Sugeno(T-S) and Mamdani -- Larsen (ML) models of fuzzy logic techniques. In the proposed controller, first membership functions are optimized by GMM and then GFM calculates the final output in single iteration i.e. with no recursions. This is highly desirable in power quality problems. The simulations demonstrate the effective and smooth performance of the power system. Comparative analysis is done between controllers based on Proportional and Integral (PI), T-S model, ML model and GMM & GFM model. Simulated results evince the superiority of the proposed hybrid controller.

In this paper, an improved particle swarm optimization (IPSO) based load frequency control (LFC) of a single area power system is presented. Although the Particle Swarm Optimization approaches have several advantages, they can still have drawbacks like local optimal trapping due to premature convergence(i.e. exploration problem). This paper proposes an improved PSO framework adopting a crossover operation scheme to increase exploitation capability of PSO. The study has been realized for control of a single area interconnected power system with IPSO optimized self-tuning PID controller. The comparison between a conventional Proportional-Integral (PI) controller and the proposed PSO based controller showed that the proposed controller can generate a better transient response for a step load change. For this application, MATLAB-Simulink software is used.

This paper presents a novel control method of Superconducting Magnetic Energy Storage (SMES) unit with a self-tuned Fuzzy Frequency Controller (FFC) associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self-tuning configuration of fuzzy frequency controller in AGC on SMES control is compared with that of optimized fixed gain PI controlled AGC. It is seen that with addition of self-tuned fuzzy frequency controller, SMES can perform a more effective primary frequency control for single area power system.

For power quality enhancement, voltage, frequency, and power flow between control areas in an interconnected power system are required to be maintained. Hence, the voltage and frequency should be continuously controlled to maintain the balance of real and reactive power during load variation. Integration of renewable energy sources (RES) in the power system leads to inertia losses and mismatches between load demand and generation capacity; hence, the load frequency controller should overcome these challenges.In this paper, a Dandelion optimizer (DO)-based tilted-integral-derivative (TID) controller is introduced for load frequency control (LFC) of a single-area power system considering renwables pentration. A single-area power system with both solar and wind power plants as renewables and reheat-thermal, hydraulic, and gas power plants as conventional power plants is modeled using the Matlab toolbox. The controller-based DO optmizer is tested under different loading variations to verify its robustness. The sperm swarm and black widow optimization algorithms are compared with the introduced algorithm to verify its superior dynamic responses for loading variation.

This paper deals with the importance of load frequency control (LFC) for single and interconnected power system. It is important to keep the frequency of the system and the inter area tie power stable. The goal of LFC is to maintain the frequency, the desired power output and to control the change in tie line power between control areas in an interconnected power system. Two different techniques have been implemented in this paper which are model predictive controller MPC and conventional proportional plus integral controller PI for LFC of single area power system as well as two area system. To investigate the powerful and robustness of model predictive control (MPC) technique for LFC problems in electric power system, time simulations is performed. The obtained results indicate that the MPC provide better damping to the single area system as well as two-area system in case of load disturbance compared with conventional PI controller. The studied single-area and two-area systems are modelled and simulated using Simulink/Matlab software.

A Fuzzy Approach of Autonomous Power Generating Systems

This paper considers the problem of load frequency control (LFC) of power systems when the states of the system are not available for implementation and in the presence of unknown disturbances. Conventional proportional observer (PO) fails to solve this problem unless the disturbances are known or can be modeled. Therefore, we provide a detailed analysis of the generalized proportional integral observer (GPIO) for load frequency control of a single area power system. This study demonstrates that the proposed observer can reliably be used. Since the suggested observer is able to estimate both the states and unknown disturbances, it can be integrated in LFC with disturbance accommodation to ensure system stability and satisfy specified performance measures. Numerical examples are given to illustrate the advantage of GPI observer-based LFC for a single area power system model.

The stability control of nominal frequency and terminal voltage in an interconnected power system (IPS) is always a challenging task for researchers. The load variation or any disturbance affects the active and reactive power demands, which badly influence the normal working of IPS. In order to maintain frequency and terminal voltage at rated values, controllers are installed at generating stations to keep these parameters within the prescribed limits by varying the active and reactive power demands. This is accomplished by load frequency control (LFC) and automatic voltage regulator (AVR) loops, which are coupled to each other. Due to the complexity of the combined AVR-LFC model, the simultaneous control of frequency and terminal voltage in an IPS requires an intelligent control strategy. The performance of IPS solely depends upon the working of the controllers. This work presents the exploration of control methodology based on a proportional integral–proportional derivative (PI-PD) controller with combined LFC-AVR in a multi-area IPS. The PI-PD controller was tuned with recently developed nature-inspired computation algorithms including the Archimedes optimization algorithm (AOA), learner performance-based behavior optimization (LPBO), and modified particle swarm optimization (MPSO). In the earlier part of this work, the proposed methodology was applied to a two-area IPS, and the output responses of LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD control schemes were compared with an existing nonlinear threshold-accepting algorithm-based PID (NLTA-PID) controller. After achieving satisfactory results in the two-area IPS, the proposed scheme was examined in a three-area IPS with combined AVR and LFC. Finally, the reliability and efficacy of the proposed methodology was investigated on a three-area IPS with LFC-AVR with variations in the system parameters over a range of  ± 50%. The simulation results and a comprehensive comparison between the controllers clearly demonstrates that the proposed control schemes including LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD are very reliable, and they can effectively stabilize the frequency and terminal voltage in a multi-area IPS with combined LFC and AVR.

Load frequency control (LFC) requires transmission of remote measurements to the control center and of control signals from the control center to the plant. Constant delays exist in the dedicated communication channel and an open communication network introduces time-varying delays. Those delays would degrade the dynamic performance of LFC and even cause instability. This paper investigates the delay-dependent stability of the LFC scheme by adopting a delay-dependent criterion and linear matrix inequalities (LMIs). The maximal delay time which allows a power system with a LFC scheme embedded to retain stable is defined as the delay margin for stability analysis. A proportional-integral (PI) controller using the area control error (ACE) as input signal is employed in the LFC scheme. Special attention is paid to the relationship between the gains of PI controller and the delay margin. Case studies are carried out based on one-area and two-area LFC schemes to demonstrate the effectiveness of the criterion. Both constant and time-varying delays are considered. Moreover, the accuracy of the criterion used is also verified by simulation studies.

BackgroundAutomatic generation control (AGC) of multi-area interconnected power system (IPS) is often designed with negligible cross-coupling between the load frequency control (LFC) and automatic voltage regulation (AVR) loops. This is because the AVR loop is considerably faster than that of LFC. However, with the introduction of slow optimal control action on the AVR, positive damping effect can be achieved on the LFC loop thereby improving the frequency control. In this paper, LFC synchronized with AVR in three-area IPS is proposed. Model predictive controller (MPC) configured in a dense distributed pattern, due to its online set-point tacking is used as the supplementary controller. The dynamics of the IPS subjected to multi-area step and random load disturbances are studied. The efficacy of the developed scheme is ascertained by simulating the disturbed system in MATLAB/Simulink.ResultsBased on the comparative analysis on the system responses, it is established that by cross-coupling the LFC loop with AVR, reductions of 66.45% and 59.09% in the frequency and tie-line power maximum deviations respectively are observed, while the respective settling times are found to be reduced by 29.68% and 22.77% when compared with the uncoordinated control scheme. In addition, the standard deviation and variance of the integral time absolute error of the system’s responses have reduced by 23.21% and 20.83% respectively compared to those obtained in a similar study.ConclusionsThe reduction in the maximum deviations and settling times in the system states indicates that introducing the voltage control via AVR loop has improved the frequency control significantly. While the lower standard deviation and variance of the integral time absolute error signify improvement in the robustness of the developed algorithm. However, this improvement is at the detriment of the controller size and computational complexity. In the uncoordinated control scheme, the control vector is one-dimensional, while in the coordinated scheme, the control vector is two-dimensional for each CA.

The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take into account possible changes in operating conditions and non-linearities in the generator unit. Moreover, it lacks robustness. This chapter studies LFC in two areas power system using PID controller. In this chapter, PID parameters are tuned using different tuning techniques. The overshoots and settling times with the proposed controllers are better than the outputs of the conventional PID controllers. This chapter uses MATLAB/SIMULINK software. Simulations are done by using the same PID parameters for the two different areas because it gives a better performance for the system frequency response than the case of using two different sets of PID parameters for the two areas. The used methods in this chapter are: (a) Particle Swarm Optimization,(b) Adaptive Weight Particle Swarm Optimization, (c) Adaptive Acceleration Coefficients based PSO (AACPSO) and (d) Adaptive Neuro Fuzzy Inference System (ANFIS). The comparison has been carried out for these different controllers for two areas power system, the study presents advanced techniques for Load Frequency Control. These proposed techniques are based on Artificial Intelligence. It gives promising results.

Information and communication technology tremendously facilitates the operation efficiency and economy of modern power systems in recent years. However, risks such as bandwidth constraints and malicious attacks threaten the secure load frequency control (LFC) of power systems. To mitigate such risks, this paper proposes distributed observer-based event-triggered LFC schemes for multi-area power systems under cyber attacks. Considering the practical situation that only local system output information may be available, distributed observer-based LFC schemes are designed. Meanwhile, to reduce the communication burden, an event-triggered mechanism is adopted to design control laws, where both static and dynamic event-triggered approaches are taken and the dynamic one is proved to be more economical in terms of control cost. Verifiable sufficient conditions are established to guarantee the stability of the closed-loop system in the presence of cyber attacks and the controller gains are explicitly derived. Finally, validation studies on a three-area interconnected power system are carried out to demonstrate the proposed control schemes. Note to Practitioners—Load frequency is a crucial index for evaluating the quality of electric energy and thus LFC has brought considerable attention in the area of power systems control. Although many achievements have been made on the LFC of multi-area power systems, the risks such as bandwidth constraints and malicious attacks affect the normal operation of LFC due to the interconnection between different power systems. To deal with these risks, this paper focuses on designing event-triggered LFC to guarantee the stability of the frequency deviation while reducing the communication burden and mitigating cyber attacks. More importantly, the proposed event-triggered LFC is designed based on an observer and can be implemented in a distributed manner, which is relatively practical in real applications. The results presented in this paper aim to provide a helpful reference for stable and secure LFC design of multi-area power systems, such that the corresponding application research can be promoted.

The modern power systems with industrial and commercial loads need to operate at constant frequency with reliable power. The load frequency control of an interconnected power system is being improved over the last few years. The goals of the LFC are to maintain stability improvement of power system. Fuzzy logic controller application of load frequency control (LFC) of a single area power system by using a fuzzy logic is presented. The study has been designed for a single area interconnected power system. The comparison between a conventional Proportional and Integral (PI) controller and the proposed artificial neural networks controller is showed that the proposed controller can generate the best dynamic response for a step load change. For this application, MATLAB-Simulink software is used.

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller.